Power System Cascading Failure Path Simulation And Risk Optimization Based On Optimal Power Flow

With the rapid development of the modern power system, and frequently happening of the cascading failures or large blackouts, the safe operation of the power system posed new challenge and requirements. The research on the path of the cascading failure and control of systematic risk has important practical significance. This paper presents a cascading failure simulating model, which is based on the OPA model and Manchester model. This model combines the advantages of the traditional OPA and Manchester model. It simulates the fast action, which means cascading failures and the changing power flow after the initial failure. It also simulates the slow action, which means the development of the system components, such as transmission lines, transformers and generators. The risk-optimal control model is set up as the algorithm kernel. Its object function is the minimization of the overload risk. The risk-optimal control model combines the risk theory and optimization theory. It takes the probabilistic characteristics of system failure and the severity of the failure into consideration, and represents the status of the system power flow well. The primal-dual interior point method is chosen to solve the nonlinear optimal question. The method has the advantages of strong convergence, high calculation effect and fine robustness, which is widely used in optimal power flow area. The program is based on Matlab programming. The power system of a city in Henan province is chosen as the test system to test the feasibility and effectiveness of the improved cascading failure model. The simulating time span is three years. The results of the test show that, the test system has the characteristic of self-organized criticality. The simulations of the cascading failure paths show the weakness of the network. The test results show the convergence, efficiency and robustness of the algorithm kernel.